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samttoo22-MewCat
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oracle

Package prompts with project files for AI-assisted CLI development.

19|3|Updated Mar 7, 2026
Search Tags:#automation#development#prompt engineering#cli#code context#ai assistant
One-click install
npx skills add https://github.com/samttoo22-MewCat/OpenSoul --skill oracle-samttoo22-mewcat
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: oracle
Source: https://github.com/samttoo22-MewCat/OpenSoul/tree/main/openclaw/skills/oracle
Command: npx skills add https://github.com/samttoo22-MewCat/OpenSoul --skill oracle-samttoo22-mewcat

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill simplifies complex CLI operations by bundling prompts and files, enabling AI models to provide context-aware assistance for development tasks.

Core Features & Use Cases

  • Contextual Code Assistance: Provides AI-driven advice and solutions by analyzing your project's codebase.
  • Efficient Workflow: Integrates with AI models to understand project structure, dependencies, and best practices.
  • Use Case: When encountering a bug, use Oracle to analyze relevant source files and receive a patch plan with suggested test cases.

Quick Start

Use the oracle skill to preview the token count for a task involving all files in the src directory.

Frequently Asked Questions about oracle

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I provide code context to an AI assistant for CLI development?▼

Providing code context for CLI development involves packaging prompts with relevant project files, enabling AI models to deliver context-aware assistance for tasks like code generation and debugging based on your specific project structure.

Can I use OpenAI and Anthropic models for code generation and debugging?▼

Yes, you can use OpenAI, Anthropic, or other LLM providers for code generation and debugging by configuring API keys, or you can opt for browser-based model execution to analyze your project files and provide patch plans.

How do I analyze source files to get a patch plan and suggested test cases?▼

Analyze source files to get a patch plan and suggested test cases by bundling the problematic files and a prompt together for contextual analysis, enabling the AI to return targeted debugging advice and suggested test cases.

Do I need to install a specific binary to automate CLI development with AI?▼

Yes, automating CLI development with AI requires installing the 'oracle' binary, which acts as the core engine to package your project files and prompts for contextual analysis by your configured LLM providers.

What is the best way to preview token counts for prompts involving a project directory?▼

The best way to preview token counts for prompts involving a project directory is to use a CLI tool that packages the directory files with your prompt, allowing you to estimate the context window size before sending it to an LLM.

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